Metadata-Version: 2.1
Name: shot_chart
Version: 1.0.11
Summary: plotting shot charts from basketball-reference.com
Home-page: https://github.com/theccalderon/shot_chart
Author: Cesar Calderon Muro
Author-email: cesar.calderon.dev@gmail.com
License: Apache Software License 2.0
Description: # Shot Chart
        > Python module to plot NBA shot chart data and distributions for players and teams and some utilities.
        
        
        This file will become your README and also the index of your documentation.
        
        ## Install
        
        `pip install shot_chart`
        
        ## How to use
        
        We first create a pandas dataframe from the source data.
        
        ```python
        shots_2019 = make_df(untar_data(URLs.SHOTS_2019))
        ```
        
        ## Listing teams for the season
        
        ```python
        list_teams(shots_2019)
        ```
        
        
        
        
            0            Atlanta
            1            Orlando
            183       Sacramento
            184             Utah
            341         Oklahoma
            343     Golden State
            511           Denver
            512      New Orleans
            675        Milwaukee
            1016        Portland
            1224         Phoenix
            1226        Brooklyn
            1412     San Antonio
            1413         Memphis
            1934         Toronto
            2119    Philadelphia
            2296       Minnesota
            2477       LA Lakers
            2655         Houston
            2656     LA Clippers
            2843       Charlotte
            3017          Boston
            3018      Washington
            3383         Detroit
            3918           Miami
            5020       Cleveland
            5535         Indiana
            6407        New York
            6410         Chicago
            8473          Dallas
            Name: team, dtype: object
        
        
        
        ## Listing players who took at least 1 shot for a particular team
        
        ```python
        list_team_players(shots_2019, 'Portland')
        ```
        
        
        
        
        <div>
        <style scoped>
            .dataframe tbody tr th:only-of-type {
                vertical-align: middle;
            }
        
            .dataframe tbody tr th {
                vertical-align: top;
            }
        
            .dataframe thead th {
                text-align: right;
            }
        </style>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>shots_by</th>
              <th>count</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>2</th>
              <td>CJ McCollum</td>
              <td>1212</td>
            </tr>
            <tr>
              <th>5</th>
              <td>Damian Lillard</td>
              <td>1158</td>
            </tr>
            <tr>
              <th>4</th>
              <td>Carmelo Anthony</td>
              <td>678</td>
            </tr>
            <tr>
              <th>7</th>
              <td>Hassan Whiteside</td>
              <td>676</td>
            </tr>
            <tr>
              <th>0</th>
              <td>Anfernee Simons</td>
              <td>522</td>
            </tr>
            <tr>
              <th>6</th>
              <td>Gary Trent</td>
              <td>349</td>
            </tr>
            <tr>
              <th>9</th>
              <td>Kent Bazemore</td>
              <td>322</td>
            </tr>
            <tr>
              <th>10</th>
              <td>Mario Hezonja</td>
              <td>188</td>
            </tr>
            <tr>
              <th>13</th>
              <td>Rodney Hood</td>
              <td>172</td>
            </tr>
            <tr>
              <th>15</th>
              <td>Trevor Ariza</td>
              <td>159</td>
            </tr>
            <tr>
              <th>12</th>
              <td>Nassir Little</td>
              <td>151</td>
            </tr>
            <tr>
              <th>14</th>
              <td>Skal Labissière</td>
              <td>147</td>
            </tr>
            <tr>
              <th>1</th>
              <td>Anthony Tolliver</td>
              <td>117</td>
            </tr>
            <tr>
              <th>3</th>
              <td>Caleb Swanigan</td>
              <td>43</td>
            </tr>
            <tr>
              <th>8</th>
              <td>Jaylen Hoard</td>
              <td>32</td>
            </tr>
            <tr>
              <th>16</th>
              <td>Wenyen Gabriel</td>
              <td>29</td>
            </tr>
            <tr>
              <th>17</th>
              <td>Zach Collins</td>
              <td>19</td>
            </tr>
            <tr>
              <th>11</th>
              <td>Moses Brown</td>
              <td>10</td>
            </tr>
          </tbody>
        </table>
        </div>
        
        
        
        ## Plotting team shot distribution
        
        ```python
        houston = TeamShots(shots_2019,"Houston")
        ```
        
        ```python
        houston.plot_shots()
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_12_0.png)
        
        
        ```python
        houston.plot_shots(date_range=((2020,1,3), (2020,1,11)))
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_13_0.png)
        
        
        Please check the extra options when using the plotting functions
        
        ```python
        portland_20191125 = TeamShots(shots_2019,"Portland")
        ```
        
        ```python
        portland_20191125.list_game_ids(2019,11,25)
        ```
        
        
        
        
        <div>
        <style scoped>
            .dataframe tbody tr th:only-of-type {
                vertical-align: middle;
            }
        
            .dataframe tbody tr th {
                vertical-align: top;
            }
        
            .dataframe thead th {
                text-align: right;
            }
        </style>
        <table border="1" class="dataframe">
          <thead>
            <tr style="text-align: right;">
              <th></th>
              <th>game_id</th>
              <th>winner</th>
              <th>loser</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <th>45560</th>
              <td>201911250CHI</td>
              <td>Portland</td>
              <td>Chicago</td>
            </tr>
          </tbody>
        </table>
        </div>
        
        
        
        ```python
        portland_20191125.plot_shots("201911250CHI")
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_17_0.png)
        
        
        ## Plotting player shot distribution
        
        ```python
        player_shots = PlayerShots(shots_2019,"Anthony Davis")
        ```
        
        ```python
        player_shots.plot_shots()
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_20_0.png)
        
        
        ```python
        dlo = PlayerShots(shots_2019,"D'Angelo Russell")
        ```
        
        ```python
        dlo.plot_shots()
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_22_0.png)
        
        
        ```python
        dlo.plot_shots(distances=["16ft","17ft","18ft","19ft","20ft","21ft","22ft","23ft","24ft","25ft","26ft"],attempt="2-pointer")
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_23_0.png)
        
        
        ```python
        dlo.plot_effective(most_or_least="most")
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_24_0.png)
        
        
        ```python
        dlo.plot_effective(most_or_least="most",exclude=["0ft"])
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_25_0.png)
        
        
        ```python
        dlo.plot_effective(most_or_least="most",min_shots="auto",exclude=['2ft'])
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_26_0.png)
        
        
        ```python
        dlo.plot_effective(most_or_least="least")
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_27_0.png)
        
        
        ```python
        dlo.plot_effective(most_or_least="least",min_shots="auto")
        ```
        
        
        ![png](https://raw.githubusercontent.com/theccalderon/shot_chart/master/docs/images/output_28_0.png)
        
        
Keywords: nba shot chart
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
